11.54 Scatter Plot Colour Shape Theme BW

20180603

set.seed(26439)
ds %>%
  sample_n(1000) %>%
  ggplot(aes(x=min_temp, y=max_temp, colour=rain_tomorrow, shape=rain_tomorrow)) +
  geom_point() +
  labs(x      = vnames["min_temp"], 
       y      = vnames["max_temp"], 
       colour = vnames["rain_tomorrow"]) +
  theme_bw() +
  theme(legend.position="bottom")

There are many circumstances where it makes sense to colour the points according to some scheme. For example, in a predictive modelling context the colour might correspond to the prediction made (yes or no). For a cluster analysis the colour might represent the cluster each point is allocated to.

A key variable of interest in the rattle::weatherAUS dataset is rain_tomorrow. By colouring the dots according to the rain_tomorrow we may begin to see relationships in the data.

The colour is added simply by specifying a further aesthetic, colour=rain_tomorrow. Different values of the variable rain_tomorrow will then be coloured differently.

---

Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2022 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0